التفاصيل البيبلوغرافية
| العنوان: |
Collaborative Production Planning Based on an Intelligent Unmanned Mining System for Open-Pit Mines in the Industry 4.0 Era |
| المؤلفون: |
Kui Liu, Bin Mei, Qing Li, Shuai Sun, Qingping Zhang |
| المصدر: |
Machines, Vol 12, Iss 6, p 419 (2024) |
| بيانات النشر: |
MDPI AG, 2024. |
| سنة النشر: |
2024 |
| المجموعة: |
LCC:Mechanical engineering and machinery |
| مصطلحات موضوعية: |
open-pit mine, unmanned excavator, unmanned mining truck, collaborative production planning, Industry 4.0, Mechanical engineering and machinery, TJ1-1570 |
| الوصف: |
Open-pit mining is a cornerstone of industrial raw material extraction, yet it is fraught with safety concerns due to rough operating conditions. The advent of Industry 4.0 has introduced advanced technologies such as AI, the IoT, and autonomous systems, setting the stage for a paradigm shift towards unmanned mining operations. With this study, we addressed the urgent need for safe and efficient production based on intelligent unmanned mining systems in open-pit mines. A collaborative production planning model was developed for an intelligent unmanned system comprising multiple excavators and mining trucks. The model is formulated to optimize multiple objectives, such as total output, equipment idle time, and transportation cost. A multi-objective optimization approach based on the genetic algorithm was employed to solve the model, ensuring a balance among conflicting objectives and identifying the best possible solutions. The computational experiments revealed that the collaborative production planning method significantly reduces equipment idle time and enhances output. Moreover, with the proposed method, by optimizing the configuration to include 6 unmanned excavators, 50 unmanned mining trucks, and 4 unloading points, a 92% reduction in excavator idle time and a 44% increase in total output were achieved. These results show the model’s potential to transform open-pit mining operations by using intelligent planning. |
| نوع الوثيقة: |
article |
| وصف الملف: |
electronic resource |
| اللغة: |
English |
| تدمد: |
2075-1702 |
| Relation: |
https://www.mdpi.com/2075-1702/12/6/419; https://doaj.org/toc/2075-1702 |
| DOI: |
10.3390/machines12060419 |
| URL الوصول: |
https://doaj.org/article/1102256c5f574413900b3d08d6dbab9f |
| رقم الانضمام: |
edsdoj.1102256c5f574413900b3d08d6dbab9f |
| قاعدة البيانات: |
Directory of Open Access Journals |